DocumentCode :
1631322
Title :
Nonlinear Function Approximation Based on Least Wilcoxon Takagi-Sugeno Fuzzy Model
Author :
Sun, Tsung-Ying ; Tsai, Shang-Jeng ; Tsai, Cheng-Han ; Huo, Chih-Li ; Liu, Chan-Cheng
Author_Institution :
Dept. of Electr. Eng., Nat. Dong Hwa Univ.
Volume :
1
fYear :
2008
Firstpage :
312
Lastpage :
317
Abstract :
The purpose of this paper is based on radial basis function neural network (RBFN) to develop a self-constructing least Wilcoxon-generalized RBFN fuzzy inference system (LW-GRBFNFIS) and applied to nonlinear function approximation and chaotic time series prediction. As is well known in statistics, the resulting linear function by using the rank-based least Wilcoxon (LW) norm approximate to linear function problems are usually robust against (or insensitive to) outliers. In addition, the Takagi-Sugeno fuzzy model and RBFN techniques have been proved the functional equivalence and successfully applied to modeling nonlinear function approximation problems. This paper introduce proposed method to improve traditional least square GRBFNFIS for nonlinear function approximation and overcome outliers´ problem. Nonlinear function approximation and chaotic time series prediction problems used to verify the proposed method. The experiments results show the proposed method can effectively solve outliers´ problems.
Keywords :
chaos; function approximation; fuzzy reasoning; fuzzy systems; least squares approximations; mathematics computing; nonlinear functions; radial basis function networks; time series; RBFN; chaotic time series prediction; fuzzy inference system; least Wilcoxon Takagi-Sugeno fuzzy model; least square method; linear function; nonlinear function approximation; radial basis function neural network; statistics; Chaos; Function approximation; Fuzzy neural networks; Fuzzy systems; Least squares approximation; Linear approximation; Radial basis function networks; Robustness; Statistics; Takagi-Sugeno model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications, 2008. ISDA '08. Eighth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-0-7695-3382-7
Type :
conf
DOI :
10.1109/ISDA.2008.261
Filename :
4696223
Link To Document :
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